Do Interest Groups Affect Immigration?

Transcription

1 European Summer Symposium in Labour Economics (ESSLE) Ammersee, September 2007 Hosted by the Institute for the Study of Labor (IZA) Do Interest Groups Affect Immigration? Anna Maria Mayda We are grateful to the following institutions for their financial and organizational support: Institute for the Study of Labor (IZA) The views expressed in this paper are those of the author(s) and not those of the funding organization(s) or of CEPR, which takes no institutional policy positions.

2 Do Interest Groups affect Immigration? Giovanni Facchini, Anna Maria Mayda and Prachi Mishra August 17, 2007 Abstract While anecdotal evidence suggests that interest groups play a key role in shaping immigration, there is no systematic empirical evidence on this issue. To motivate our analysis, we develop a simple theoretical model where migration policy is the result of the interaction between organized groups with conflicting interests towards labor flows. We evaluate the key predictions of the model using a new, industry-level dataset from the United States that we construct by combining information on the total number of immigrants and H1B visas with data on lobbying expenditures associated with immigration. We find robust evidence that both pro- and anti-immigration interest groups play a statistically significant and economically relevant role in shaping migration across sectors. Barriers to migration are lower in sectors in which business lobbies incur larger lobbying expenditures and higher in sectors where labor unions are more important. JEL classification: F22, J61. Keywords: Immigration, Immigration Policy, Interest Groups, Political Economy. The authors would like to thank seminar participants at the AEA Meetings in Chicago, Georgetown University, IMF, Midwest Political Science Meetings for useful comments. Jose Manuel Romero provided excellent research assistance. University of Essex, Universita degli Studi di Milano, CEPR, LdA and CES-Ifo; gfacch@essex.ac.uk. Georgetown University, CEPR, LdA and IZA; amm223@georgetown.edu. Research Department, International Monetary Fund; PMishra@imf.org. 1

3 Immigration policy today is driven by businesses that need more workers skilled and unskilled, legal and illegal [...] During the annual debate on H1B visas two years ago, Silicon Valley executives trooped before Congress, warning of a Y2K computer disaster unless the number of H1B visas was increased. Goldsborough (2000) 1 Introduction On May 1, 2006, over a million demonstrators filled US TV screens. They were mainly Latinos, who marched peacefully through America s cities in the hope that Congress would finally introduce legislations to overhaul the country s immigration policy. A year later, an innovative, bipartisan legislation was proposed by Senators Ted Kennedy and John Kyl, but since it was unveiled, it has been stoned from all sides (The Economist, May 24, 2007). President Bush, referring to this proposal, has proclaimed that I view this as an historic opportunity for Congress to act, for Congress to replace a system that is not working with one that we believe will work a lot better, (White House, June 26, 2007). Even though many observers have deemed the status quo unacceptable, no measures have been voted yet. What determines US immigration policy today? In particular, are political-economy factors important in shaping immigration to the United States? Do these drivers work along sector (industry) lines, that is do sector-specific factors with greater political influence succeed in changing migration policy towards their benefit? In particular, what is the role played by industry-specific interest groups? In this paper, we address these issues by analyzing the impact of political organization by business lobbies and workers associations on the structure of migration to the U.S. across sectors between 1998 and This paper represents, to the best of our knowledge, the first study to provide systematic empirical evidence on the political-economy determinants of immigration to the U.S. and, in particular, on the role played by interest groups. A vast theoretical and empirical literature considers the political-economy determinants of trade policy trying to explain the political constraints that work against free trade. In contrast, the literature on the political economy of migration policy and outcomes is very thin and mainly theoretical. So far, in analyzing the determinants of international labor flows, the migration literature has mostly focused on supply factors, i.e. factors which affect the willingness of workers to move across borders. On the other hand, the analysis of the drivers of the demand side of international migration, the most important being migration policies 2

4 in developed countries, has not received as much attention. 1 This is in spite of the fact that, as trade restrictions have been drastically reduced, the benefits from the elimination of existing trade barriers are much smaller than the gains that could be achieved by freeing international migration. 2 This gap in the literature is very surprising and can be partly explained by the unavailability of data. The purpose of this paper is to offer a contribution towards filling this gap. There exists abundant anecdotal evidence which suggests that political-economy factors and, in particular, interest groups play a key role in shaping U.S. immigration. Starting from the very birth of organized labor and for most of their history, unions have been actively engaged in efforts to limit inflows of foreign workers. The enactment of the first legislative measure to systematically limit immigration from a specific country the Chinese Exclusion Act of 1882 was the result of the efforts of the newly founded Federation of Organized Trade and Labor Unions. Similarly, the American Federation of Labor (AFL) played an important role in the introduction of the Literacy Test provision in the 1917 Immigration Act, with the explicit intent to screen and reduce the inflow of unskilled workers in the U.S labor force (Briggs (1998), page 125). More recently, the AFL-CIO supported measures to reduce illegal immigration, that culminated in the 1986 Immigration Reform and Control Act. At the same time, complementarities among production factors are fundamental in understanding the behavior of pressure groups. In the past, active subsidization of immigration has been demanded and obtained by business associations in many labor scarce countries, as has been extensively documented by Timmer and Williamson (1996). The importance of business lobbies is also consistent with more recent anecdotal evidence. For instance, in the aftermath of the 2006 midterm elections, the vice- president of Technet, a lobbying group for technology companies, stressed once again that the main goal of the reforms proposed by her group is the relaxation of migration policy constraints. 3 1 For example, Borjas (1994) points out that the literature does not yet provide a systematic analysis of the factors that generate the host country demand function for immigrants. (page 1693). See section 2 for a discussion of the related literature. 2 A recent World Bank study estimates that the benefits to poor countries of rich countries allowing only a 3 percent rise in their labor force by relaxing migration restrictions is US$300 billion per year (Pritchett 2006). For similar results see also Hamilton and Whalley (1984). 3 In particular, the proposed reforms are aimed at...increasing the number of H1B visas granted annually to foreign workers employed temporarily at U.S. companies; granting employment-based visas to workers whose H1B visas are about to expire but whose application for lawful permanent residency (commonly known as a green card ) is backlogged; and allowing foreign workers who earn advanced degrees at U.S. colleges and universities to stay and work in the United States once they graduate. CIO, December Available at 3

5 The paper starts by developing a simple theoretical model that motivates our empirical analysis. We consider a multi sector, small open economy in which migration policy is the result of the interaction between organized groups with conflicting interests over international labor movements. In particular, in each sector, there are two complementary factors - labor (which is internationally mobile), and capital (which is fixed). The owners of each factor are modeled as investing resources to influence the determination of policy towards labor mobility. We show that in equilibrium, in a given sector, the amount of protection afforded to labor i.e., the restrictiveness of the migration policy adopted by the government depends on both the lobbying expenditures made by organized labor, as well as on the expenditures made by capital (which is its complement). In particular, if labor in a sector spends larger amounts, this will ceteris paribus imply higher levels of protection from foreign inflows of workers and, hence, lower the equilibrium number of immigrants. At the same time, if organized business owners spend higher amounts, this will ceteris paribus make migration policy in that sector less restrictive and, therefore, increase the number of immigrants. Next, we evaluate the predictions of the model using a new, U.S. industry level dataset that we create by combining information on the total number of immigrants and H1B visas with data on the political activities of organized groups, both in favor and against an increase in migration. We take advantage of a novel dataset developed by the Center for Responsive Politics, that allows us to identify lobbying expenditures, by targeted policy area, for the period between 1998 and We are thus able to use information on business lobbying expenditures that are specifically channeled towards shaping immigration policy. This represents a substantial improvement in the quality of the data relative to the existing international economics literature which has used, instead, political action committees (PAC) contributions. First, PAC contributions represent only a small fraction (10%) of targeted political activity, the remainder being made up by lobbying expenditures. Second, PAC contributions cannot be disaggregated by issue and thus, cannot be easily linked to a particular policy. Finally, in order to proxy for the political organization of anti-migration lobbying groups, we use data on workers union membership rates across sectors, from the Current Population Survey. Our findings are consistent with the predictions of the theoretical model. In particular, we show that both pro and anti migration interest groups play a statistically significant and economically relevant role in shaping migration across sectors. We find that barriers to migration are ceteris paribus higher in sectors where labor unions are more important, and lower in those sectors in which business lobbies are more active. Our preferred esti- 4

6 mates suggest that a 10% increase in the size of lobbying expenditures by business groups is associated with a 1.8% larger number of immigrants, while a one-percentage-point increase in union density for example, moving from 10 to 11 percentage points, which amounts to a 10% increase in union membership rate reduces it by 1.3%. The results are robust to the introduction, in the estimating equation, of a number of industry-level control variables (e.g. output, prices, origin country effects, etc.) and to addressing endogeneity issues with an instrumental-variable estimation strategy. The remainder of the paper is organized as follows. Section 2 reviews the relevant literature. Section 3 presents the theoretical model, while section 4 describes the data on lobbying expenditure, in particular in relation to PAC contributions data. Section 5 provides a description of the other data used in the empirical analysis, while the results of our empirical analysis are reported in section 6. Section 7 concludes the paper. 2 Literature While a large body of theoretical and empirical literature is devoted to understanding the political economy of protection in international trade, there are only few studies that analyze the politics of distortions in international factor movements. Furthermore, while in international trade the protection for sale model of Grossman and Helpman (1994) has emerged as the leading framework to understand the commercial policy formation process, a unified framework to understand migration policy has yet to emerge. 4 In what follows, we first review the existing theoretical literature on the political economy of migration policy, starting with direct democracy models and turning next to settings in which the lobbying activities of organized groups play a key role. Second, we discuss the (scarce) empirical evidence on these issues. In a seminal contribution, Benhabib (1996) considers the human capital requirements that would be imposed on potential immigrants by an income-maximizing polity under majority voting. Output is modeled using a constant returns to scale production function combining labor with human (or physical) capital. The median voter chooses to admit individuals who supply a set of factors that are complementary to her own endowment. As a result, if the median voter is unskilled, he will choose a policy that sets a lower bound on the skill level of the immigrants, that is only skilled foreigners will be admitted. On the other 4 For an overview of this literature, see the surveys by Rodrik (1995), Helpman (1997), and Gawande and Krishna (2003). Facchini (2004) surveys instead the literature on political economy models of trade and factor mobility. 5

7 hand, if the median voter is highly educated, he will set an upper bound on the skill level of the immigrants, and thus will be in favor of admitting only individuals with low levels of education. The main shortcoming of this analysis is that the optimal policy does not identify the actual size of the inflows. This is clearly at odds with the policies followed by countries all around the world. In our model the presence of a fixed factor will instead allow us to determine the politically optimal number of immigrants to be admitted. A different solution to this problem has been proposed by Ortega (2005), who extends Benhabib s model to a dynamic setting to explore the trade off between the short run economic impact of immigration and its medium to long run political effect. In particular, while immigration affects only the labor market in the current period, in the future it also influences the political balance of the destination country, as the descendants of migrants gain the right to vote. As a result, on the one hand, skilled natives prefer an immigration policy that admits unskilled foreign workers since, due to complementarities in production, this policy will increase the skilled wage. On the other, the arrival of unskilled immigrants and the persistency of skill levels across generations can give rise to a situation in which unskilled workers gain the political majority and, therefore, vote for policies that benefit them as a group. Thus, through the political channel, skilled natives prefer an immigration policy that admits skilled foreign workers. The interplay between these two forces allows Ortega to characterize under which conditions an equilibrium migration quota might arise, i.e. to derive a prediction in terms of the size of the migration inflows. 5 The paper in the migration literature that is most closely related to our work is Facchini and Willmann (2005). Using the menu auction framework pioneered by Bernheim and Whinston (1986), the authors model the determination of policies towards international factor mobility as the result of the interaction between organized groups and an elected politician. Using a one good multiple factors framework, Facchini and Willmann (2005) find that policies depend on both whether a production factor is represented or not by a lobby and on the degree of substitutability/complementarity between factors. Our model differs from their work in two ways. On the one hand, we explicitly link equilibrium policies to actual lobbying expenditures. Secondly, we consider a multi sector environment, which enables us to exploit the newly available data by industry on lobbying expenditures. 6 5 The median voter approach has also been used in the large literature analyzing the impact of immigration on the recipient country s welfare system. Among the many papers see Mazza and van Winden (1996), Razin, Sadka, and Swagel (2002), Scholten and Thum (1996), Razin and Sadka (1999) and the literature surveyed in the recent volume by Krieger (2005). 6 Recently, a small theoretical literature has emerged explicitly modeling the role played by organized groups in shaping migration policy in a setting with imperfectly competitive factor markets. Amegashie 6

8 The economics literature lacks a systematic empirical analysis of the political-economy factors that affect contemporary migration. 7 While the empirical literature on individual attitudes towards immigrants is closely related to the topic, 8 it does not examine how attitudes translate into migration (policy) outcomes. The only empirical work we could find that indirectly looks at the political-economy determinants of migration policy/outcomes is Hanson and Spilimbergo (2001). This paper focuses on U.S. border enforcement and shows that enforcement softens when sectors using illegal immigrants expand. The authors suggest that sectors that benefit greatly from lower border enforcement lobby politicians on the issue, while sectors that benefit modestly are less politically active. The main purpose of this paper is to evaluate this conjecture that lobbying affects immigration policy though in the broader context of overall immigration to the United States. 3 Theoretical model Consider a small open economy consisting of n + 1 sectors, populated by a unit mass of individuals. The output of sector zero is the numeraire and is produced using labor according to an identity production function, i.e. X 0 = L 0. The output of all other sectors is produced using sector specific labor, which we assume to be internationally mobile. 9 The production technology in each sector exhibits diminishing returns to labor, and we denote by ω i the domestic return to labor in sector i. As usual, diminishing returns can be attributed to the presence of a fixed factor in each sector (Dixit and Norman 1980). We will call this factor capital and denote the aggregate reward to the specific factor employed in sector i by π i. For simplicity, we assume that free trade in goods prevails and we normalize the international price for each commodity, setting it equal to one. Similarly, we assume that the return in the international market to each type of labor is also equal to one. Any difference between the domestic factor return ω i and the international return will be explained by the policies implemented by the domestic government. (2004) and Bellettini and Berti Ceroni (2006) are examples of this approach. Our analysis will instead be based on competitive factor markets, where no unemployment occurs in equilibrium. 7 The literature offers historical accounts of the political economy of immigration restrictions between the end of the XIX century and the beginning of the XX century (Goldin 1994, Timmer and Williamson 1996). 8 See, for example, Scheve and Slaughter (2001), Mayda (2006), O Rourke and Sinnott (2004), Hanson, Scheve, and Slaughter (2007), Facchini and Mayda (2006). 9 There is substantial evidence supporting this view. For instance Friedberg (2001), among others, finds a significant positive relationship between source and destination country sector employment for Russian immigrants to Israel in the nineties. 7

9 Consumers are characterized by a separable, quasi linear utility function that takes the following form: u(x) = x 0 + n u i (x i ) (1) An individual maximizing this utility given an income I will have a demand d i (p i ) for each non-numeraire good, while the demand for the numeraire good is given by d 0 = I n i=1 p id i (p i ). The indirect utility of our representative consumer is thus given by V = I + i s i(p i ), where i s i(p i ) = i u i(d i (p i )) p i d i (p i ) is the consumer surplus. Notice that, by assuming a small open economy that trades freely in final goods, the consumer surplus of each agent is not going to be affected by changes in factor returns brought about by government policies (i.e., changes in factor returns do not affect goods prices). Let l i denote the total domestic supply of labor of type i, i {0, 1,...n} available in the economy, while L i (ω i ) is the demand for this factor. Restrictions 10 to the physical relocation of people across countries often take the form of a (binding) quota, accompanied by a tax (i.e., a differential fiscal treatment for immigrants vis a vis natives 11 ), resulting in the immigrant retaining part of the surplus associated with the relocation (i.e., the difference between the wage prevailing in the country of destination and the country of origin). As a result, the fiscal revenues associated with the presence of binding quotas q i in sectors i {1,..., n} are equal to i=1 T (q) = i γ i (ω i (q i ) 1)(L i (ω i (q i )) l i ) (2) where ω i (q i ) is the wage that prevails in the Host country as a result of the introduction of a binding quota, and L i (ω(q i )) is the corresponding employment level. The parameter γ i [0, 1] represents instead the share of the rent associated with the immigration quota that is captured by the government of the receiving country, while (1 γ i ) is the fraction of the wage premium (ω i (q i ) 1) associated with migration that is retained by the relocating migrant. The fiscal revenues associated with the quota cum tax introduced by the government 10 Of course, policies could also be used to promote immigration. This has been for instance the case in many labor scarce economies in the nineteenth century like Brazil and Argentina, as Timmer and Williamson (1996) have pointed out. Within the framework of the model, policies of this type would take the form of immigration subsidies. For simplicity we will not model this type of instruments explicitly as in the recent U.S. experience they have hardly been used. 11 The US tax code for instance configures a differential treatment between residents and non residents. 8

10 are lump sum rebated to all citizens of the country we are considering. Each domestic citizen supplies one unit of labor specific to the numeraire sector and at most one unit of a factor (capital or labor) specific to any non-numeraire sector. Since the size of the domestic population is normalized to one, the welfare of the agents supplying labor in sector i is equal to V il = ω i (q i )l i + α il [1 + T (q) + i s i (p i )], (3) where the first term is the return to sector i specific labor, α il is the share of the population that owns labor used in the production of output i and, finally, 1 is the return to labor in the numeraire sector. The welfare of agents supplying the fixed factor (capital) is instead given by V ik = π i (q i ) + α ik [1 + T (q) + i s i (p i )], (4) where π i (q i ) is the return to capital in sector i and α ik is the share of the population that owns sector i specific capital. The first best policy in this model is obtained by maximizing the welfare of all natives, i.e. W (q) = (V ik + V il ) (5) i and, as can be easily shown, this involves free labor mobility. Intuitively, starting from a scenario with less than free labor mobility, immigration reduces wages, but the loss to domestic workers is less than the gains to domestic capital owners (see Borjas 1995 for a graphical exposition). Hence, it is optimal to admit all foreign workers willing to relocate to the country. In other words, the first-best quota qi set by the government is such that q i m i (1, p i ) = L i (1, p i ) l i (6) If we bring in directly the quantities of the specific factors in the production structure and let k i be the amount of specific factor employed in sector i, the first best number of migrants m i (1, k i, p i ) is ceteris paribus an increasing function of the stock of capital k i available in sector i. Similarly, an increase in the relative price of the good produced in sector i leads to an increase in the first best number of migrants in the sector. In both cases, the increase in the number of migrants is brought about by an outward shift in the labor demand curve in the sector. 9

11 Recent rational choice analyses have pointed out how interest groups can directly participate in the political process in at least two ways. On the one hand, they provide substantive information to policy makers; on the other, at least in the United States, they offer financial incentives: this setting postulates a simple quid pro quo view of the relationship between an elected politician and the interest group. In the international economics literature the most influential approach, pioneered by Grossman and Helpman (1994), has emphasized the second view and in particular the role of direct campaign contributions in shaping policies. 12 Formally, Grossman and Helpman (1994) have proposed an analytical foundation for a political support function that is based on the politician including pressure groups campaign contributions directly in its objective function. While this approach has been very successful and can be thought of as the current paradigm in the endogenous trade literature, an important feature of this model is that the existence of a lobby matters in equilibrium, and not its actual contribution level... (Eicher and Osang 2002). 13 Furthermore, the Grossman and Helpman (1994) model ignores the important informational channel through which lobbies can also influence policy and the data shows that, if anything, businesses might perceive informational lobbying to be at least as important as campaign contributions. 14 To characterize the link between equilibrium policy outcomes and contributions and to allow for a more general role of lobbies, we have decided to use a protection formation function approach. According to this view, government policy is simply a function of the expenditures undertaken by pro and anti immigration groups, and we refrain from spelling out more in detail how interest groups actually affect the political process. Inspired by the pioneering contributions of Findlay and Wellisz (1982), we model measures towards labor mobility in 12 More generally, our view is that the reward to a politician for a political favor might take much more complicated forms than direct campaign contributions. For instance, politicians at the end of their career become themselves active lobbyists and, in some cases, are able to earn substantial rewards for carrying out their activities in this role. According to the CRP website, Lobbying firms were still able to find 129 former members of Congress willing to lobby on everything from postal rates to defense appropriations. Former Rep. Bob Livingston (R-La.), who was once days away from becoming Speaker of the House, drummed up $1.14 million in business in his first year as an independent lobbyist. 13 Technically, one can show that the equilibrium contributions paid by the lobbies to the government are a function of the bargaining power of the agents vis a vis the principal. As Grossman and Helpman (1994) point out, if there is only one lobby interacting with the elected politician, the lobby will capture all the surplus from the relationship, keeping the policy maker at the same welfare level as in a world with free trade and no payments carried out by the lobby. On the other hand, if all sectors are organized, the policy implemented will be free trade - thus no favor will be received by any lobby in the political equilibrium - and the government will capture all the surplus from the relationship (page ). For more on this important issue, see also Goldberg and Maggi (1999) and Dixit, Grossman, and Helpman (1997). 14 See Milyo, Primo, and Groseclose (2000) and the discussion contained in section 4. For recent contributions theoretical models of informational lobbying, see Bennedsen and Feldman (2006), Dahm and Porteiro (2004) and Lohmann (1995). 10

12 each sector as the result of expenditures by a pro migration lobby (made up by capital owners) and by an anti migration lobby (made up by workers). In particular, we will carry out our analysis assuming that ω i (q i ) 1 = λ(e il ) 2 (1 λ)(e ik ) 2, where λ represents the weight of labor in the protection function and (1 λ) the weight of capital. Notice that the protection function is increasing in the expenditures of organized workers and decreasing with the expenditures undertaken by the owners of capital. Furthermore, we assume increasing returns to lobbying, to reflect the real world observation that larger donors command disproportionately greater influence (Eicher and Osang 2002). The two lobby then play a non-cooperative game where they choose the amount to pay in order to maximize their net welfare, given by Ω ik (q i ) = V ik (q i ) E ik Ω il (q i ) = V il (q i ) E il Assuming for simplicity that γ i = 1 for all i, 15 the two first order conditions are given by [ ] T (ω(q)) ωi q i L i + α ik = 1 (7) ω i q i E [ ] ik T (ω(q)) ωi q i l i + α il = 1 (8) ω i q i E il To interpret equations (7) and (8), notice that the first term on the left hand side in brackets represents the impact of a change in the return to labor on the welfare of the lobby, and the product of the second and third terms represents the marginal effect of one dollar of expenditure on the return to labor. Thus, the left hand side equals the marginal benefit brought about to the lobby by a dollar of expenditure, and that has to be equal to the marginal cost 1 in the right hand side. Assume that the domestic labor demand is linear, i.e. that it takes the form L i = L bω i (9) and that, for simplicity, the ownership of capital in the population is highly concentrated (α ik = 0 for all i). 16 Solving simultaneously the system of equations given by (7) and (8), 15 Assuming impartial rent capturing, i.e. γ i < 1, complicates the algebra without changing the main result. For an analysis that includes imperfect capturing, see Facchini and Willmann (2005) and Facchini and Testa (2006). 16 Formally, we are assuming that the production function in each sector takes the form y i = L b L i 1 2b L2 i, where L, b > 0. The corresponding profit function (return to the specific factor) is then given by π = L 2 2b + b 2 ω2 i Lω i. 11

13 the quota chosen by the domestic government is equal to q i = L b 2 l i 2 [ ] αil + 1 α il + 1 2α il [ 1 λ λ ] E ik E il (10) Thus, ceteris paribus, sectors in which unions are more active and spend larger amounts have higher protection (i.e., smaller quotas) granted to domestic labor, while sectors where capital s expenditures are higher will have less restrictive migration policies, i.e. quotas. larger How likely is it that the observed number of migrants is the result of the working of the political-economy forces we have modeled? In other words, could it be the case that the actual number of migrants is the result of shocks occurring on the supply side of migration, rather than of the policy actually implemented by the Host country? To answer this question, consider the possibility that, after a restrictive quota has been introduced, a supply shock occurs in the international market, that increases the wage prevailing in the rest of the world from 1 to w (Figure 1). This could be, for example, the result of a technological improvement in the source country that lifts the average wage individuals can earn by staying put. Better opportunities in the rest of the world imply that the potential migrant will need to re evaluate his decision to relocate. In particular, in our simple model he will be moving only if the wage he can earn in the destination country is higher than the wage he can fetch in the rest of the world. Thus, as a result of the upward shift in the international labor supply (from L S w to L S w ) two possible scenarios can arise. They are illustrated in panel (a) and (b) of Figure 1 where L d and l S are, respectively, the labor demand and the domestic labor supply in the destination country, and q is the quota set by the government. Panel (a) describes the case in which the original quota set by the Host country continues to be binding after the shock. In this situation, the wage w q determined by the quota is still above the wage prevailing in the rest of the world after the shock, and the number of migrants effectively admitted to the Host country continues to be determined by the Host country s restrictive policy. In panel (b) instead, the shock to the international factor price is substantial and the wage prevailing in the international market is above w q, the quota determined wage. As a result, the quota is no longer binding, and the number of migrants actually willing to relocate to the Host country is lower than the one set by the quota and equal to L d (ω ) l S, while the equilibrium wage prevailing in the destination country is given by ω. In this case, the political economy forces no longer play a role is shaping the volume of migrants, which is instead purely determined by market forces, i.e. by the intersection between domestic labor demand and international labor supply. Therefore, it is important 12

14 to point out that, for the supply side considerations to play a role in shaping the equilibrium outcome in this simple model, a very large shock must occur, that makes the policy choice of the host government irrelevant. Whether supply side considerations play a role is thus an empirical matter, which will be addressed in section 6. 4 Lobbying expenditures In the United States, special interest groups can legally influence the policy formation process through two main channels. On the one hand, they can offer campaign finance contributions, while on the other they can carry out lobbying activities. Campaign finance contributions and, in particular, contributions by political action committees (PAC) have been the focus of the literature (see for example Snyder 1990, Goldberg and Maggi 1999, Gawande and Bandyopadhyay 2000). Yet PAC contributions are not the only route by which interest groups money might be able to influence policy makers and, given the existing limits on the size of PAC contributions (see Milyo, Primo and Groseclose, 2000 for details), it is likely that they are not the most important one. It has been pointed out that lobbying expenditures are of... an order of magnitude greater than total PAC expenditure (Milyo, Primo, and Groseclose 2000). Hence, it is surprising that so few empirical papers have looked at the effectiveness of lobbying activities in shaping policy outcomes. To the best of our knowledge, only a recent article by de Figueiredo and Silverman (2006) has taken a close look at this issue. 17 One important reason for this relative lack of interest is that, while PAC contributions data has been readily available and PACs can be linked to a corporate or industry sponsor, only with the introduction of the Lobbying Disclosure Act of 1995, individuals and organizations have been required to provide a substantial amount of information on their lobbying activities. Starting from 1996, all lobbyists must now file semi annual reports to the Secretary of the Senate s Office of Public Records (SOPR), listing the name of each client (firm) and the total income they have received from each of them. At the same time, all firms with in-house lobbying departments or hired lobbyists are required to file similar reports stating the dollar amount they have spent. 18 Importantly, legislation requires the disclosure not only 17 In particular, the authors find that for a university with representation in the House or Senate appropriations committees, a 10% increase in lobbying yields a 3 to 4% increase in earmark grants obtained by the university. 18 A firm could be a subsidiary of a parent firm or the parent firm itself if there are no subsidiaries. In the former (latter) case, CRP provides lobbying expenditures data at the subsidiary (parent-firm) level. Notice 13

15 of the dollar amounts actually received/spent, but also of the issues for which lobbying is carried out (Table A1 shows a list of 76 issues at least one of which has to be entered by the filer). Finally, the reports must also state which chamber of Congress and which executive departments or agencies were contacted. A sample lobbying report filed by Microsoft for its lobbying activities between January - June, 2005 is shown in Table A2. Thus, the new legislation provides access to a wealth of new information, and the purpose of this paper is to use this information to assess how lobbying influences migration policy and outcomes. The data on lobbying expenditures is compiled by the Center for Responsive Politics (CRP) in Washington D.C., using the semi-annual lobbying disclosure reports, which are posted in its website. The reports analyzed by CRP cover lobbying activity that took place from 1998 through 2006 (due to unavailability of data on other variables, we restrict the empirical analysis in this paper to the period ). Annual lobbying expenditures and incomes (of lobbying firms) are calculated by adding mid-year totals and year-end totals. Whenever there is a discrepancy between data on income and expenditures, CRP uses information from lobbying reports on expenditure. CRP also matches each firm to an industry (Table A3 shows the list of about 90 industries used by CRP). Further details about the data on lobbying expenditures are discussed in the Data Appendix. We define overall or total lobbying expenditures in an industry as the sum of lobbying expenditures by all firms in that industry on any issue. The lobbying expenditures for immigration-related issues in an industry are calculated using a three-step procedure. First, only those firms are considered which list immigration as an issue in their lobbying report. The lobbying dataset comprises an unbalanced panel of a total of about 15,000 firms, out of which about 700 list immigration as an issue in at least one year. Second, the total expenditure of these firms is split equally between the issues they lobbied for. Finally, these firm-level expenditures on immigration are aggregated for all firms within that industry. As shown in Table 1, between 1999 and 2004, interest groups have spent on average about 3.8 billion U.S. dollars per political cycle on targeted political activity, which includes PAC campaign contributions and lobbying expenditures. 19 Lobbying expenditures represent by far the bulk of all interest groups money (close to ninety percent). Therefore, the focus of the that different subsidiaries of the same parent firm can be associated with different industries. Finally, the list of firms includes associations of firms. 19 We follow here the literature that excludes from targeted-political-activity figures soft money contributions, which went to parties for general party building activities not directly related to Federal campaigns; in addition, soft money contributions were not subject to any limits and cannot be associated with any particular interest or issue (see Milyo, Primo and Groseclose, 2000 and Tripathi, Ansolabehere, and Snyder 2002). Soft money contributions have been banned by the 2002 Bipartisan Campaign Reform Act. 14

16 international economics literature on the role of PAC contributions in shaping policies might be limiting for at least two reasons. On the one hand, PAC contributions represent only a tiny fraction of interest groups targeted political activity (10 percent), and any analysis of the role of lobbies in shaping policy based on only these figures could be misleading. Second, linking campaign contributions to particular policy issues is very difficult and often requires some ad-hoc assumption. For instance, in their pioneering work on the estimation of Grossman and Helpman (1994) protection for sale model, Goldberg and Maggi (1999) have used minimum PAC expenditure thresholds to identify whether a sector was organized or not from the point of view of trade policy determination. The availability of direct information on the main purposes of the lobbying activity provides a clear advantage in linking lobbying expenditures to actual outcomes. The importance of doing so is shown in Figure 2 (on average over three election cycles), where on the top panel we have scatter plots of overall lobbying expenditures and PAC contributions, while on the bottom panel we have a plot of lobbying expenditures associated with immigration policy and PAC contributions. We find a very high correlation between total lobbying expenditures and PAC contributions across sectors. The correlations (not shown) are qualitatively similar when we look year-by-year. This result is consistent with the political science literature and may suggest that PAC contributions are integral to groups lobbying efforts and even buy access.(tripathi, Ansolabehere, and Snyder 2002). In contrast, the very low correlation between PAC contributions and lobbying expenses for migration policy is striking. It suggests that, if we were to use the data on PAC contributions assuming they are associated with immigration we might obtain misleading results; hence the use of our new dataset is fundamental in order to clearly identify how lobbying affects migration policy. 5 Other Data The information on lobbying expenditures is merged with data from the Integrated Public Use Microdata Series - Current Population Survey (IPUMS-CPS) for the years between 1998 and The IPUMS-CPS data set is based on the March Annual Demographic File and Income Supplement to the Current Population Survey (CPS). It contains individual-level information on a range of socio-economic characteristics, such as: education level; industry; employment status; birthplace; year of immigration; nativity (foreign-born vs. native-born); union membership; wages and salary income. 15

17 The analysis is restricted to individuals aged who participate in the civilian labor force. Natives are defined as native-born respondents, regardless of whether their parents are native-born or foreign-born. Immigrants are defined as foreign-born individuals, either naturalized or non-citizens. Respondents born abroad who are citizens only by virtue of being born to U.S. parents are excluded from both groups. Following the theoretical model, the workers are differentiated according to their industry of employment. The variable ind1950 in the IPUMS-CPS is used to obtain information on the industry in which the worker performs or performed in his most recent job, if unemployed at the time of the survey his or her primary occupation. This variable uses the 1950 Census Bureau industrial classification system consistently across the years. The list of CPS industries is shown in Table A4. 20 The IPUMS-CPS data set contains information at the individual level. The following variables are constructed by aggregating the individual-level data to the industry level total number of immigrants, total number of natives, fraction of union members, fraction of unemployed, and mean weekly earnings. To construct the latter three variables, we restrict the sample to natives. The fraction of natives who are union members in each industry represents our measure of political organization of labor in that industry. The weekly earnings are deflated using the U.S. GDP deflator from the IMF. All the variables are constructed using sampling weights as recommended by the IPUMS-CPS. We also gather data on other control variables at the industry level. The data on output, price and (inward) foreign direct investment (FDI) at the industry level is from the Bureau of Economic Analysis. Gross output represents the market value of an industry s production in current dollars, and the price index is based on year 2000 = 100. The data on domestic capital (in millions of current dollars) by industry is from the Annual Capital Expenditures Survey (ACES) carried out by the U.S. Census Bureau. Gross output, prices and FDI are available for all years between 1998 and 2005, but the capital data is not yet available for The data on output, price, FDI and domestic capital is defined for industries according to the 1997 North American Industrial Classification System (NAICS). Finally, we collect data on two additional variables to measure push factors for migrants in source countries. First, we construct a measure of shocks in source countries, which is industry specific. We use information on developing country-years in which there was a shock as captured by a war, earthquake, wind storm or drought. The data on wars is from a database compiled by the Heidelberg Institute for International Conflict Research and the 20 In the census bureau classification, non-profit membership organizations (or unions) are treated as a separate industry (CPS code = 897). We drop these, since unions are assumed to be anti-migration in the model and are analyzed separately from pro-business lobbies. 16

18 World Bank; the data on other shocks is from Ramcharan (2007). In particular, the industryspecific measure of shocks is equal to a weighted average of the shocks in each origin country, with weights equal to the share of immigrants in that industry from each origin country. The second measure of push factors in source countries is the average (monthly) earnings in Mexico which, in the period considered in our sample, is by far the most important country of origin of U.S. immigrants. 21 The data on Mexican earnings is taken from the monthly industrial surveys for 205 manufacturing industries (Encuesta Industrial Mensual 2). As for the dependent variable of our analysis, in addition to using information on the number of immigrants, we also use data on the number of visas at the industry level, which is a more direct measure of immigration policy. The only type of visas for which information is available at the industry level is the employment-based H1B visas. The data is obtained from the United States Citizenship and Immigration Services (USCIS), which is part of the Department of Homeland Security (DHS). Under the H1B program, specialty workers are permitted to be employed for up to three years with the possibility of an extension not exceeding three more years. In order to sponsor a foreign worker under the H1B program, an employer must first file an application with the Department of Labor. Once the Department of Labor certifies the application, U.S. employers file a petition with the USCIS to sponsor the foreign worker for an H1B visa. The data from the USCIS is, thus, based on the total number of petitions which have been approved. The petition may be filed to sponsor the foreign worker for an initial period of H1B employment or to extend the authorized stay. The data on H1B petitions approved at the firm level is aggregated by the USCIS at the industry level according to the NAICS classification. In order to match the CPS data with that on lobbying expenditures and on the other variables and create an industry-level dataset, we construct separate concordances of (i) CRP, (ii) NAICS and (iii) Encuesta Industrial Mensual 2 classifications to the 1950 Census Bureau industrial classification. Concordances are complicated by the fact that there is not always a one-to-one correspondence between two sectors in any two classifications. In the case where there are, for example, multiple CPS industries corresponding to a given CRP industry, the lobbying expenditures are divided among CPS industries according to the share of natives in each CPS industry. Next, in order to take into account the cases where one CPS industry is matched to many CRP industries (which is often the case), the data is summed and collapsed at the CPS industry level. Similar procedures are adopted for 21 In 2004, the 10.5 million Mexican immigrants living in the United States were 31 percent of the U.S. foreign-born population (Hanson 2006). 17

19 matching the data on output, price, FDI, domestic capital and the number of H1B visas to the CPS dataset. Using the number of immigrants as the dependent variable, our dataset covers about digit industries. The sample with the number of visas is slightly smaller and includes approximately 120 observations. 5.1 Summary statistics Figure 3 presents the evolution of real lobbying expenditures over time. The nominal expenditures are deflated using the U.S. GDP deflator constructed by the IMF. The left scale shows the overall expenditures and the right scale shows the expenditures for issues related to immigration. While the overall real lobbying expenditure has grown by over 40 percent from US$1.4 bn to US$2.1 bn between 1998 and 2005, the expenditure for immigration-related issues has grown by only about 10 percent from US$19 to 21 mn over the same period. The share of immigration in overall lobbying expenditures has been roughly constant at about 1%. In comparison, expenditures on trade comprise 4-5% of overall lobbying expenditures. On average, an industry spent US$16 mn in 1998 on lobbying activities, an amount which increased to US$23 mn in For immigration, the average expenditure by an industry was approximately constant at US$0.3 mn throughout the period (Table 2). Figure 4 shows the top 10 industries according to expenditures on lobbying for immigration in 2005, according to the CRP industry classification. Hospital & Nursing Homes and Computers/Internet are the top spenders on lobbying for immigration. Among the top 10 spenders we also find Agricultural Services/Products and Education. Figure 5 shows instead the top 10 sectors (by the Census Bureau classification) with the highest number of immigrants in Construction, Eating and Drinking Places and Business Services are, not surprisingly, at the top of the list, with a stock of 2.5, 1.7 and 1.2 million immigrants respectively in Medical and Other Health Services, Hospitals and Agriculture also appear at the top of the list. It is interesting to note that at least four industries with very high expenditures on immigration (agriculture, education, business services and hospitals) are also among those with the highest number of immigrants. Before proceeding to the regression analysis, it is instructive to document bivariate relationships between key variables using simple scatter plots. Figure 6 suggests a positive correlation between lobbying expenditures for immigration and the number of immigrants (both variables are, in this graph, averaged across the years ). We find very similar evidence year by year, between 1998 and 2005 (not shown). Thus, these basic scatter plots suggest that sectors with larger lobbying expenditures on immigration are characterized by a 18